Particle Tracking Velocimetry

This work examines experimentally how a viscous incompressible liquid modifies the behavior of a granular bulk in avalanche. A large and a small laboratory flume of identical length-to-width ratio have been constructed to initiate granular avalanche. Two types of monatomic spheres were used, preserving the ratio between the particle diameter and the flume width, with or without water to prepare

The purpose of this study is twofold: 1) to explore the feasible implementation of whole-field visualization techniques such as infrared thermometry, particle tracking velocimetry, and high speed shadowgraphy to study subcooled boiling flow through a vertical square channel with a single heated wall and 2) to provide subcooled boiling flow experimental measurements based on the methodology developed in this work. To fulfill the first objective, a series of sensitivity studies and uncertainty analyses was performed, from which recommendations for the proper implementation of these visualization techniques for the study of two-phase flows are given. The purpose of the second objective is to provide reliable information that can be used for the validation of CFD simulations and for the improvement and development of turbulence models under subcooled boiling conditions. Unique in the presented experimental results is the whole-field simultaneous measurement of turbulence characteristics...

A whole-field three-dimensional (3D) particle tracking velocimetry (PTV) tool for diagnostics in fluid mechanics is presented. Specifically, it is demonstrated why and when PTV is the natural choice in 3D applications compared to particle image velocimetry (PIV). Three different tracking methods are investigated, namely the nearest neighbour, the neural network and the relaxation method. In order to demonstrate the use of PTV for 3D applications, the selected tracking schemes are implemented for use with the defocusing digital particle image velocimetry (DDPIV) technique. The performance of the tracking algorithms is evaluated based on synthetic 3D information. Furthermore, the potential benefit of a merging between the PIV and PTV approaches is explored within the DDPIV framework. The results show that the relaxation tracking method is the most robust and efficient, while the combined PIV/PTV analysis brings significant improvements solely with the neural network scheme. In terms of errors, PTV is found to be more sensitive to particle reconstruction errors than the DDPIV cross-correlation analysis.

Acceleration and spatial velocity gradients are obtained simultaneously in an isotropic turbulent flow via three dimensional particle tracking velocimetry. We observe two distinct populations of intense acceleration events: one in flow regions of strong strain and another in regions of strong vorticity. Geometrical alignments with respect to vorticity vector and to the strain eigenvectors, curvature of Lagrangian trajectories and of streamlines for total acceleration, a=Du/Dt and for its convective part, ac=(u⋅∇)u, are studied in detail. We discriminate the alignment features of total and convective acceleration statistics, which are genuine features of turbulent nature from those of kinematic nature. We find pronounced alignment of acceleration with vorticity. Similarly, a and especially ac are predominantly aligned at 45°with the most stretching and compressing eigenvectors of the rate of the strain tensor, λ1, and λ3, respectively. Via autocorrelation functions of acceleration, conditioned on preferential directions, the vorticity vector field is found to play an important role as an ordering reference axis for acceleration orientation. Associating a velocity–acceleration structure function with an energy flux gives a clear indication that a strong energy flux occurs via compression in strain dominated events and via stretching in vorticity dominated events.► Acceleration structure is revealed in respect to the local spatial velocity gradients. ► Genuine turbulence properties are distinguished from the kinematics of velocity gradients. ► High acceleration events are probable due to strong vorticity and due to strong rate of strain events. ► “Vortex trapping” and “jet colliding” are comparable in creating strong acceleration events. ► 3D-PTV is substantially improved to reach the high fidelity data on spatial/temporal velocity gradients.

It is necessary to have a comprehensive understanding of the flow mechanisms within drip irrigation emitters to design emitters that have a high anti-clogging performance. The use of computational fluid dynamics (CFD) to research the flow characteristics is appropriate because the labyrinth flow path is narrow and its boundary is complex. In this paper, a CFD for numeric model was developed for numerical simulation of the velocity distribution and turbulence intensity distributions within labyrinth emitters. A two-dimensional digital particle-tracking velocimetry (2D-DPIV) visual display system of the full flow fields was also constructed using plain laser inducement fluorescence velocity measurement technology, custom-made fluorescent particles and a plane model of the emitters. The object lens of a microscope was fitted to a conventional charge coupled device (CCD) camera to overcome the contradiction problems between the image viewing area and resolution power within the flow path. The measured turbulence and velocity distribution characteristics within the labyrinth flow path were in good agreement with the calculated CFD results. This enabled the optimal emitter design patterns to be determined based on the hydraulic characteristics and clogging resistance in the labyrinth flow path.

 We describe a new neural network designed to solve the correspondence problem of particle-tracking velocimetry. Given two successive pictures of marker-particles suspended in a fluid, it matches their images by approximately duplicating the fluid motion. We present the results of efficiency tests that reveal the excellence of its performance and its stability with respect to the presence of unmatchable particle images. We compare its success rate in image matching to that of the neural network of Grant and Pan (1995), and observe that it produces better results when the flows have more important changes in direction. It has the important advantages over the latter, of being better adapted to benefit from parallel computing, and of being self-starting, i.e. of not requiring to be taught about the fluid flow in advance.

In this research, a technique of simultaneously measuring the velocity and the temperature in micro-scale flow is proposed. This method uses particle tracking velocimetry (PTV) for measuring the velocity and laser induced fluorescence (LIF) for measuring the temperature. To measure the accurate velocity and temperature, images for PTV and for LIF are separated by using two light sources and a shutter which is synchronized with a camera. By using only one camera, measurement system can be simplified and the error from complicate optical system can be minimized. Error analyses regarding the concentrations of fluorescent dye and particle and the light source fluctuation are also conducted. It is found that the error of the temperature and the velocity highly depends on the concentration of fluorescent particles which are used for PTV. This technique is applied to the simultaneous measurement of the velocity and the temperature in the electrokinetic flow. It is found that the velocity and temperature vary with the electric field strength and the concentration of electrolyte. Also, it is found that the effect of Joule heating increases the electrokinetic velocity.

Cross-correlation Particle Image Velocimetry (PIV) has become a well known and widely used experimental technique. It has been already documented that difficulties arise resolving velocity structures smaller than the interrogation window. This is caused by signal averaging over this window. A new cross-correlation PIV method that eliminates this restriction is presented. The new method brings some other enhancements, such as the ability to deal with large velocity gradients, seeding density inhomogeneities, and high dispersion in the brightness of the particles. The final result is a method with a remarkable capability for accurately resolving small scale structures in the flow, down to a few times the mean distance between particles. When compared to particle tracking velocimetry, the new method is capable of obtaining measurements at high seeding density concentrations. Therefore, better overall performance is obtained, especially with the limited resolutions of video CCDs. In thi...

An experimental study designed to determine free-surface characteristics of a turbulent flow, generated by jets that emerge from the bottom of the pool, is described. Particle Tracking Velocimetry at the free-surface was used to measure the velocity field, vorticity field and two-dimensional divergence (Hanratty’s β). While the high magnitudes of β did occur at similar locations to high surface vorticity, the scale of these maximal and minimal are approximately 1/3 of the scales of surface vorticity. This indicates that the scales of vorticity and β may not be correlated, or at least are correlated at a substantial multiplicative reduction. The relationship between β and liquid film coefficient is discussed. For flows where transfer is dominated by all frequencies of β, K L ∼ (Dβ rms )1/2 is sufficient. However, there are flows where the large eddies are more important, and a spectra of β needs to be computed, according to McCready et al’s [12] relation K L ∼ (DS βmax )1/2. In this case, a methodology is needed for transferring wave number spectra of β to frequency spectra in tanks without a significant flow, in order to estimate K L . In our experiments, 1% of the turbulent kinetic energy was chosen to simulate similar results in a flume.

Turbulent resuspension, a process of lifting solid particles from the bottom by turbulent flow, is ubiquitous in environmental and industrial applications. The process is a sequence of events that start with an incipient motion of the particle being dislodged from its place, continue as sliding or rolling on the surface, ending with the particle being detached from the surface and lifted up into the flow. In this study the focus is on the resuspension of solid spherical particles with the density comparable to that of the fluid and the diameter comparable with the Kolmogorov length scale. We track their motion during the lift-off events in an oscillating grid turbulent flow. We measure simultaneously the Lagrangian trajectories both of the particles freely moving along the bottom smooth wall and of the surrounding flow tracers. Different force terms acting on particles were estimated based on particle motion and local flow parameters. The results shown that: i) the lift force is dominant; ii) drag force on freely moving particles is less relevant in this type of resuspension; iii) the Basset (history or viscous-unsteady) force is a non-negligible component and plays an im-*

D-Particle Tracking Velocimetry (PTV) is one of the most flexible techniques for flow measurement, which allows the determination of three-dimensional velocity fields. Research activities in this field performed by the Institute of Geodesy and Photogrammetry at ETH Zurich for more than a decade have reached a status of an operational and reliable measurement method used in hydrodynamics and space applications.

A single-camera coupled particle tracking velocimetry-laser-induced fluorescence (PTV-LIF) technique and validation results from an experiment in a neutrally buoyant turbulent round jet are presented. The single-camera implementation allows the use of a 12-bit 60 frame-per-second 1024×1024 pixel digital CCD camera capable of streaming images in real time to hard disk resulting in very accurate PTV and LIF with excellent spatial and temporal resolution. The technique is capable of determining the turbulent scalar flux, as well as the Reynolds stress and mean and fluctuating velocity and concentration fields. Details of dye choice, corrections for attenuation due to dye, particles and water, photobleaching, vignetting, CCD calibration, and illumination power and geometry corrections are presented. Detailed results from the validation experiment confirm the accuracy and resolution of the technique, and in particular, the ability to measure . Bootstrap 95% uncertainty intervals are presented for the calculated statistics.

 A single-camera coupled particle tracking velocimetry–laser-induced fluorescence (PTV–LIF) technique and validation results from an experiment in a neutrally buoyant turbulent round jet are presented. The single-camera implementation allows the use of a 12-bit 60 frame-per-second 1024 × 1024 pixel digital CCD camera capable of streaming images in real time to hard disk resulting in very accurate PTV and LIF with excellent spatial and temporal resolution. The technique is capable of determining the turbulent scalar flux, as well as the Reynolds stress and mean and fluctuating velocity and concentration fields. Details of dye choice, corrections for attenuation due to dye, particles and water, photobleaching, vignetting, CCD calibration, and illumination power and geometry corrections are presented. Detailed results from the validation experiment confirm the accuracy and resolution of the technique, and in particular, the ability to measure . Bootstrap 95% uncertainty intervals are presented for the calculated statistics.

A data validation technique for 3-D particle tracking velocimetry is proposed. Rule based fuzzy logic system has been used. In the proposed scheme, the PTV pairing results will be provided as an input to the validating system. Then, velocity vectors of the particles in the neighborhood are measured, in terms of velocity gradient, direction and magnitude. The distance between vector midpoints, difference in vector magnitudes, average value of vector magnitude and the sum of the squares of the differences of the x, y and z-components of the velocity vectors are used as reference parameters for evaluation. Depending upon the combination of the values of these different parameters the fuzzy logic system will check how much the vectors are likely to be declared as true vectors in terms of numerical parameter called confidence. Higher value of confidence shows that the vectors under consideration as true while the vectors are likely to be erroneous for lower value of confidence. The resul...